| Title |
Deep learning workflow in radiology: a primer
|
|---|---|
| Published in |
Insights into Imaging, February 2020
|
| DOI | 10.1186/s13244-019-0832-5 |
| Pubmed ID | |
| Authors |
Emmanuel Montagnon, Milena Cerny, Alexandre Cadrin-Chênevert, Vincent Hamilton, Thomas Derennes, André Ilinca, Franck Vandenbroucke-Menu, Simon Turcotte, Samuel Kadoury, An Tang |
X Demographics
The data shown below were collected from the profiles of 58 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 14 | 24% |
| United Kingdom | 3 | 5% |
| Netherlands | 3 | 5% |
| Italy | 3 | 5% |
| Spain | 2 | 3% |
| Brazil | 2 | 3% |
| Switzerland | 2 | 3% |
| Germany | 2 | 3% |
| United States | 2 | 3% |
| Other | 9 | 16% |
| Unknown | 16 | 28% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 33 | 57% |
| Practitioners (doctors, other healthcare professionals) | 12 | 21% |
| Scientists | 11 | 19% |
| Science communicators (journalists, bloggers, editors) | 2 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 301 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 301 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 37 | 12% |
| Student > Ph. D. Student | 32 | 11% |
| Student > Master | 25 | 8% |
| Other | 24 | 8% |
| Student > Bachelor | 21 | 7% |
| Other | 45 | 15% |
| Unknown | 117 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 54 | 18% |
| Computer Science | 42 | 14% |
| Engineering | 23 | 8% |
| Nursing and Health Professions | 7 | 2% |
| Physics and Astronomy | 6 | 2% |
| Other | 38 | 13% |
| Unknown | 131 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 39. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 November 2020.
All research outputs
#1,015,609
of 24,833,726 outputs
Outputs from Insights into Imaging
#36
of 1,141 outputs
Outputs of similar age
#25,819
of 467,734 outputs
Outputs of similar age from Insights into Imaging
#2
of 34 outputs
Altmetric has tracked 24,833,726 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,141 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 467,734 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.